Advancing Geological Zoning Based on Wavelet Transform Analysis Improves Production Screening in Iranian Oilfields

As time passes, world’s energy demand makes petroleum men to drill more and deeper wells to access much oil and gas for arising energy requirement. This also needs more focusing on selection of super productive intervals based on available data for more production. Fracturesplay crucial role in production of oil and gas by introducing super conductive path ways to the porous medium. Thus, fracture detection is a key step for characterization and modeling of reservoirs for optimizing production by shooting to the casing right in fracture muster points.Detection of fractures is possible with earlier approaches which most often need costly data like core permeability or image logs. Permeability based approaches due to need for permeability profile along the wellbore will come with erroneous prediction either because of lack of precise permeability profile or user judgment. They are reservoir quality index (RQI), Flow Zone Indicator (FZI), Free Fluid Index (FFI) and Tiab Hydraulic flow unit (HT). On the other hand, although image log is a certain way to see wellbore wall, it did not exist in majority of elder drilled wells. Thus, it is not possible to find fracture networks in these wells and it should be done with available data (full set logs). Presence of fracture will cause sharp changes in some rock reservoir properties like porosity, resistivity and saturation. Wavelet Transform Analysis (WTA) is sensitive to changes in the inlet signal and can be employed for fracture detection. Considering petrophysical data as inlet signals, fractures can be highlighted with change in near wellbore resistivity in the fairly fixed lithology. Decomposition of such signals after removing high frequency noises shows very valuable data hidden in the low frequency part of the original signal. This approach is employed for finding fracture muster points in one of Middle Eastern oil wells. After de-noising, results show good match with interpreted FMI of under studied well. Application of this approach can eliminate running of image logs and also can help for finding hot spots for perforation or well path design of directional wells.